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Identification of susceptibility modules and genes for peri-implantitis compared to periodontitis within the same host environment using weighted gene co-expression network analysis

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주제분류치의학

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Purpose: This study aimed to identify new susceptibility modules and genes by analyzing the transcriptional profiles of peri-implantitis and periodontitis within the same host environment, using weighted gene co-expression network analysis (WGCNA). Methods: Gingival tissue samples were collected from 10 patients, each presenting with both periodontitis and peri-implantitis sites, and were used for RNA sequencing. We conducted WGCNA to identify key modules that showed distinct transcriptional expression profiles between periodontitis and peri-implantitis. Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses were carried out using R software. Genes with an adjusted P value greater than 0.05 were excluded from gene selection using the Pearson correlation method. Results: A total of 2,226 regulated genes were identified, and those with similar expression patterns were grouped into 5 color-coded functional modules using WGCNA. Among these, 3 modules showed distinct differences in expression profiles between peri-implantitis and periodontitis. The turquoise and yellow modules were associated with upregulation in peri implantitis, while the blue module was linked to periodontitis. This finding suggests that peri-implantitis and periodontitis have significantly different transcriptional signatures. Over-representation analysis was conducted to explore the component genes of the established modules. The top-ranked genes, selected based on their network connectivity within the modules, were identified using DESeq2 and were considered hub genes. Conclusions: WGCNA revealed distinct modular gene patterns in peri-implantitis and periodontitis, highlighting transcriptional differences between the 2 conditions. Notably, we identified 10 key genes from each of the 3 modules—the blue module associated with periodontitis-dominant pathways, and the turquoise and yellow modules associated with peri-implantitis-dominant pathways. The hub genes and pathways unveiled in this research are likely key contributors to the progression of peri-implantitis and warrant further exploration as promising candidates.

Abstract

Purpose: This study aimed to identify new susceptibility modules and genes by analyzing the transcriptional profiles of peri-implantitis and periodontitis within the same host environment, using weighted gene co-expression network analysis (WGCNA). Methods: Gingival tissue samples were collected from 10 patients, each presenting with both periodontitis and peri-implantitis sites, and were used for RNA sequencing. We conducted WGCNA to identify key modules that showed distinct transcriptional expression profiles between periodontitis and peri-implantitis. Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses were carried out using R software. Genes with an adjusted P value greater than 0.05 were excluded from gene selection using the Pearson correlation method. Results: A total of 2,226 regulated genes were identified, and those with similar expression patterns were grouped into 5 color-coded functional modules using WGCNA. Among these, 3 modules showed distinct differences in expression profiles between peri-implantitis and periodontitis. The turquoise and yellow modules were associated with upregulation in peri implantitis, while the blue module was linked to periodontitis. This finding suggests that peri-implantitis and periodontitis have significantly different transcriptional signatures. Over-representation analysis was conducted to explore the component genes of the established modules. The top-ranked genes, selected based on their network connectivity within the modules, were identified using DESeq2 and were considered hub genes. Conclusions: WGCNA revealed distinct modular gene patterns in peri-implantitis and periodontitis, highlighting transcriptional differences between the 2 conditions. Notably, we identified 10 key genes from each of the 3 modules—the blue module associated with periodontitis-dominant pathways, and the turquoise and yellow modules associated with peri-implantitis-dominant pathways. The hub genes and pathways unveiled in this research are likely key contributors to the progression of peri-implantitis and warrant further exploration as promising candidates.

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